>> The issue isn't machine time, it's that an AI system consisting of many 
>> modules has to have one canonical format for representing content, so that 
>> the modules can work together; so versatility is a key virtue. 

Do the many modules have to have one canonical format for representing content 
-- or do they have to have one canonical format for *communicating* content?

I think that you need to resign yourself to the fact that many of the modules 
are going to have *very* different internal representations.

>>  I'm suggesting predicate calculus (or some variant thereof) is the best 
>> all-round candidate for a canonical format. 

I would argue that predicate calculus is just a 
simplified-to-the-point-of-pretending-to-be-rigorous human language.  Of 
course, the problem with predicate calculus is the vocabulary (or lack of 
specification thereof).

The brain co-evolved with language.  I suspect that the easiest minimal 
canonical communicating format is going to be something pretty close to an even 
more rigorously syntactically defined Simple English 
(http://en.wikipedia.org/wiki/Wikipedia:Simple_English_Wikipedia).

  ----- Original Message ----- 
  From: Russell Wallace 
  To: [email protected] 
  Sent: Tuesday, March 13, 2007 1:24 PM
  Subject: Re: [agi] Logical representation


  On 3/13/07, Mark Waser <[EMAIL PROTECTED]> wrote:

    Human-readable is an interesting term . . . .  Is a picture human-readable? 
 I think that you would argue not (in this context, obviously).

  Well, a picture is (in some domains) human-readable - and I think tools that 
display certain kinds of information in picture format will be essential. But 
it's not human-maintainable, and there are a lot of things it's simply not 
suitable for. 



    All of the things that you name as non-human-readable certainly can be 
converted (albeit, extremely inefficiently) to a human readable format 
(sufficient to reproduce the item in question with no further information -- 
given sufficient time).

  The issue isn't machine time, it's that an AI system consisting of many 
modules has to have one canonical format for representing content, so that the 
modules can work together; so versatility is a key virtue. Vector of floats for 
example is a perfectly good format for early stages of vision processing - it 
can easily be converted into a human-readable picture. But it's not a good 
representation for most other purposes. I'm suggesting predicate calculus (or 
some variant thereof) is the best all-round candidate for a canonical format. 



    Arguably, the *only* human readable format is a human language (in which 
you can then explain predicate calculus, SQL, and XML as well as everything you 
label as non-human-readable).

  Well, the chosen format also has to be machine-readable, so as always we have 
to compromise.


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